Project description
New platform to ensure data lakes float securely
With so much data all around us, there are data sets too large for traditional management and analysis tools. As the sources of this Big Data continue to grow, data lakes are helping to solve the challenges by providing centralised secure repositories to store, manage, analyse and share structured and unstructured data. But most of these data are sensitive and cannot be widely distributed or even just used without strong protection. In this context, the ERC-funded CryptAnalytics project will develop a unified platform for secure analytics as business services in many situations. The project’s solution is a response to a growing need for privacy-preserving analytics, which are crucial for the data economy.
Objective
Big data and data lakes are gold mines for data scientists with tons of applications to finance, medicine, economics, etc. But most of these data are quite sensitive and cannot be widely distributed or even just used without strong protection. One is thus facing the huge dilemma of having to make the choice between highly valuable analytics and privacy. The ERC CryptoCloud project has designed several primitives perfectly well-suited to such situations. They are quite powerful but also highly technical for appropriate deployment at scale. The European start-up Cosmian has been interested in our tools, and we have already started a fruitful collaboration. The main goal of this CryptAnalytics project is to develop a unified platform that will allow dealing with many situations, for secure analytics as business services. This will accelerate the development of Cosmian, giving a major competitive advantage on the fast emerging market of data analytics, with strong privacy guarantees by design. Companies are realizing the incredible value of privacy-preserving analytics. As a result, the number of business use-cases is exploding, but each application is a new challenge in itself, with new kinds of evaluations, new privacy concerns, and different amounts of data.
Fields of science
Keywords
Programme(s)
Funding Scheme
ERC-POC - Proof of Concept GrantHost institution
75794 Paris
France